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Applications of smart technologies in logistics and transport: A review

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  • Chung, Sai-Ho

Abstract

The emergence of smart technologies (STs) is inducing significant transformation in logistics and transport nowadays. STs refer to the applications of artificial intelligence and data science technologies, such as machine learning, big data, to create cognitive awareness (autonomous) of an object with the support of information and communication technologies such as IoT and Blockchain. Currently, many applications of STs have demonstrated potential promise in enhancing the efficiency and effectiveness in various logistics operations and transportation systems. Further, these new advanced technologies create huge modelling challenges to traditional optimization approaches and thus create rich new research opportunities for developing new optimization methodologies in the field of logistics and transport studies. As such, our aim is to conduct a comprehensive review on noteworthy contributions made in the applications of STs in improving logistics operations and transportation network efficiency. More importantly, we explore and discuss the technical difficulties encountered by researchers in the development of optimization methodologies caused by the applications of STs. Finally, we conclude the studies with suggestions for future research.

Suggested Citation

  • Chung, Sai-Ho, 2021. "Applications of smart technologies in logistics and transport: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
  • Handle: RePEc:eee:transe:v:153:y:2021:i:c:s1366554521002192
    DOI: 10.1016/j.tre.2021.102455
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    as
    1. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    2. Timothy F. Welch & Alyas Widita, 2019. "Big data in public transportation: a review of sources and methods," Transport Reviews, Taylor & Francis Journals, vol. 39(6), pages 795-818, November.
    3. Dong Yang & Lingxiao Wu & Shuaian Wang & Haiying Jia & Kevin X. Li, 2019. "How big data enriches maritime research – a critical review of Automatic Identification System (AIS) data applications," Transport Reviews, Taylor & Francis Journals, vol. 39(6), pages 755-773, November.
    4. Debjit Roy & Ananth Krishnamurthy & Sunderesh Heragu & Charles Malmborg, 2015. "Stochastic models for unit-load operations in warehouse systems with autonomous vehicles," Annals of Operations Research, Springer, vol. 231(1), pages 129-155, August.
    5. Sun, Xuting & Chung, Sai-Ho & Choi, Tsan-Ming & Sheu, Jiuh-Biing & Ma, Hoi Lam, 2020. "Combating lead-time uncertainty in global supply chain's shipment-assignment: Is it wise to be risk-averse?," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 406-434.
    6. Chang Liu & Yongfu Feng & Dongtao Lin & Liang Wu & Min Guo, 2020. "Iot based laundry services: an application of big data analytics, intelligent logistics management, and machine learning techniques," International Journal of Production Research, Taylor & Francis Journals, vol. 58(17), pages 5113-5131, September.
    7. Liu, Weihua & George Shanthikumar, J. & Tae-Woo Lee, Paul & Li, Xiang & Zhou, Li, 2021. "Special issue editorial: Smart supply chains and intelligent logistics services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    8. Simoni, Michele D. & Kutanoglu, Erhan & Claudel, Christian G., 2020. "Optimization and analysis of a robot-assisted last mile delivery system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    9. Shen, Yu & Zhang, Hongmou & Zhao, Jinhua, 2018. "Integrating shared autonomous vehicle in public transportation system: A supply-side simulation of the first-mile service in Singapore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 125-136.
    10. Zijian He & Vaneet Aggarwal & Shimon Y. Nof, 2018. "Differentiated service policy in smart warehouse automation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(22), pages 6956-6970, November.
    11. Boysen, Nils & Schwerdfeger, Stefan & Weidinger, Felix, 2018. "Scheduling last-mile deliveries with truck-based autonomous robots," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1085-1099.
    12. Roy, Debjit & Krishnamurthy, Ananth & Heragu, Sunderesh & Malmborg, Charles, 2015. "Queuing models to analyze dwell-point and cross-aisle location in autonomous vehicle-based warehouse systems," European Journal of Operational Research, Elsevier, vol. 242(1), pages 72-87.
    13. Choi, Tsan-Ming, 2019. "Blockchain-technology-supported platforms for diamond authentication and certification in luxury supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 17-29.
    14. Sameer Hasija & Zuo-Jun Max Shen & Chung-Piaw Teo, 2020. "Smart City Operations: Modeling Challenges and Opportunities," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 203-213, January.
    15. Kaffash, Sepideh & Nguyen, An Truong & Zhu, Joe, 2021. "Big data algorithms and applications in intelligent transportation system: A review and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 231(C).
    16. Caitlin D. Cottrill & Sybil Derrible, 2015. "Leveraging Big Data for the Development of Transport Sustainability Indicators," Journal of Urban Technology, Taylor & Francis Journals, vol. 22(1), pages 45-64, January.
    17. Khan, Waqar Ahmed & Chung, Sai-Ho & Ma, Hoi-Lam & Liu, Shi Qiang & Chan, Ching Yuen, 2019. "A novel self-organizing constructive neural network for estimating aircraft trip fuel consumption," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 132(C), pages 72-96.
    18. Tang, Christopher S. & Veelenturf, Lucas P., 2019. "The strategic role of logistics in the industry 4.0 era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 1-11.
    19. Gunasekaran, Angappa & Subramanian, Nachiappan & Papadopoulos, Thanos, 2017. "Information technology for competitive advantage within logistics and supply chains: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 99(C), pages 14-33.
    20. Seokgi Lee & Yuncheol Kang & Vittaldas V. Prabhu, 2016. "Smart logistics: distributed control of green crowdsourced parcel services," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 6956-6968, December.
    21. Kamble, Sachin S. & Gunasekaran, Angappa & Gawankar, Shradha A., 2020. "Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications," International Journal of Production Economics, Elsevier, vol. 219(C), pages 179-194.
    22. Chee, Pei Nen Esther & Susilo, Yusak O. & Wong, Yiik Diew, 2020. "Determinants of intention-to-use first-/last-mile automated bus service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 350-375.
    23. Pan, Xiongfeng & Li, Mengna & Wang, Mengyang & Zong, Tianjiao & Song, Malin, 2020. "The effects of a Smart Logistics policy on carbon emissions in China: A difference-in-differences analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    24. Sven Winkelhaus & Eric H. Grosse, 2020. "Logistics 4.0: a systematic review towards a new logistics system," International Journal of Production Research, Taylor & Francis Journals, vol. 58(1), pages 18-43, January.
    25. Yan Shang & David Dunson & Jing-Sheng Song, 2017. "Exploiting Big Data in Logistics Risk Assessment via Bayesian Nonparametrics," Operations Research, INFORMS, vol. 65(6), pages 1574-1588, December.
    26. Jason Hawkins & Khandker Nurul Habib, 2019. "Integrated models of land use and transportation for the autonomous vehicle revolution," Transport Reviews, Taylor & Francis Journals, vol. 39(1), pages 66-83, January.
    27. Sun, X.T. & Chung, S.H. & Chan, Felix T.S. & Wang, Zheng, 2018. "The impact of liner shipping unreliability on the production–distribution scheduling of a decentralized manufacturing system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 242-269.
    28. Boysen, Nils & Schwerdfeger, Stefan & Weidinger, Felix, 2018. "Scheduling last-mile deliveries with truck-based autonomous robots," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 126189, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    29. Zhong, Ray Y. & Huang, George Q. & Lan, Shulin & Dai, Q.Y. & Chen, Xu & Zhang, T., 2015. "A big data approach for logistics trajectory discovery from RFID-enabled production data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 260-272.
    30. Kitjacharoenchai, Patchara & Min, Byung-Cheol & Lee, Seokcheon, 2020. "Two echelon vehicle routing problem with drones in last mile delivery," International Journal of Production Economics, Elsevier, vol. 225(C).
    31. Govindan, Kannan & Soleimani, Hamed & Kannan, Devika, 2015. "Reverse logistics and closed-loop supply chain: A comprehensive review to explore the future," European Journal of Operational Research, Elsevier, vol. 240(3), pages 603-626.
    32. Winkelhaus, S. & Grosse, E. H., 2020. "Logistics 4.0: a systematic review towards a new logistics system," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 118539, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    33. Tsan‐Ming Choi & Stein W. Wallace & Yulan Wang, 2018. "Big Data Analytics in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1868-1883, October.
    34. Mohamed Ben-Daya & Elkafi Hassini & Zied Bahroun, 2019. "Internet of things and supply chain management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4719-4742, August.
    35. Chen, Zhibin & He, Fang & Yin, Yafeng & Du, Yuchuan, 2017. "Optimal design of autonomous vehicle zones in transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 44-61.
    36. George Baryannis & Sahar Validi & Samir Dani & Grigoris Antoniou, 2019. "Supply chain risk management and artificial intelligence: state of the art and future research directions," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 2179-2202, April.
    37. Jun, Wang Ki & Lee, Min-Kyu & Choi, Jae Young, 2018. "Impact of the smart port industry on the Korean national economy using input-output analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 480-493.
    38. Mehrdokht Pournader & Yangyan Shi & Stefan Seuring & S.C. Lenny Koh, 2020. "Blockchain applications in supply chains, transport and logistics: a systematic review of the literature," International Journal of Production Research, Taylor & Francis Journals, vol. 58(7), pages 2063-2081, April.
    39. Sai Ho Chung & Hoi Lam Ma & Hing Kai Chan, 2017. "Cascading Delay Risk of Airline Workforce Deployments with Crew Pairing and Schedule Optimization," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1443-1458, August.
    40. Becker, Till & Illigen, Christoph & McKelvey, Bill & Hülsmann, Michael & Windt, Katja, 2016. "Using an agent-based neural-network computational model to improve product routing in a logistics facility," International Journal of Production Economics, Elsevier, vol. 174(C), pages 156-167.
    41. Choi, Tsan-Ming & Wen, Xin & Sun, Xuting & Chung, Sai-Ho, 2019. "The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 178-191.
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